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Course Allocation via Stable Matching

Author

Listed:
  • Franz Diebold
  • Haris Aziz
  • Martin Bichler
  • Florian Matthes
  • Alexander Schneider

Abstract

The allocation of students to courses is a wide-spread and repeated task in higher education, often accomplished by a simple first-come first-served (FCFS) procedure. FCFS is neither stable nor strategy-proof, however. The Nobel Prize in Economic Sciences was awarded to Al Roth and Lloyd Shapley for their work on the theory of stable allocations. This theory was influential in many areas, but found surprisingly little application in course allocation as of yet. In this paper, different approaches for course allocation with a focus on appropriate stable matching mechanisms are surveyed. Two such mechanisms are discussed in more detail, the Gale-Shapley student optimal stable mechanism (SOSM) and the efficiency adjusted deferred acceptance mechanism (EADAM). EADAM can be seen as a fundamental recent contribution which recovers efficiency losses from SOSM at the expense of strategy-proofness. In addition to these two important mechanisms, a survey of recent extensions with respect to the assignment of schedules of courses rather than individual courses is provided. The survey of the theoretical literature is complemented with results of a field experiment, which help understand the benefits of stable matching mechanisms in course allocation applications. Copyright Springer Fachmedien Wiesbaden 2014

Suggested Citation

  • Franz Diebold & Haris Aziz & Martin Bichler & Florian Matthes & Alexander Schneider, 2014. "Course Allocation via Stable Matching," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(2), pages 97-110, April.
    • Handle: RePEc:spr:binfse:v:6:y:2014:i:2:p:97-110
    DOI: 10.1007/s12599-014-0316-6
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    References listed on IDEAS

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    Cited by:

    1. Diebold, Franz & Bichler, Martin, 2017. "Matching with indifferences: A comparison of algorithms in the context of course allocation," European Journal of Operational Research, Elsevier, vol. 260(1), pages 268-282.
    2. Eric Budish & Ruiquan Gao & Abraham Othman & Aviad Rubinstein & Qianfan Zhang, 2023. "Practical algorithms and experimentally validated incentives for equilibrium-based fair division (A-CEEI)," Papers 2305.11406, arXiv.org, revised May 2023.
    3. Martin Bichler & Soeren Merting, 2021. "Randomized Scheduling Mechanisms: Assigning Course Seats in a Fair and Efficient Way," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3540-3559, October.
    4. Katarina Cechlarova & Bettina Klaus & David F.Manlove, 2018. "Pareto optimal matchings of students to courses in the presence of prerequisites," Cahiers de Recherches Economiques du Département d'économie 16.04, Université de Lausanne, Faculté des HEC, Département d’économie.
    5. Hoda Atef Yekta & Robert Day, 2020. "Optimization-based Mechanisms for the Course Allocation Problem," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 641-660, July.

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    Keywords

    Matching; Stability; Efficiency;
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